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AWS Certified Specialty MLS-C01 最もよくて最新で資料を提供いたします。

AmazonのMLS-C01 - AWS Certified Machine Learning - Specialty資格講座認定試験の最新教育資料はRadiatoripermotoriの専門チームが研究し続けてついに登場し、多くの人の夢が実現させることができます。 Amazon MLS-C01 専門トレーリング「AWS Certified Machine Learning - Specialty」認証試験に合格することが簡単ではなくて、Amazon MLS-C01 専門トレーリング証明書は君にとってはIT業界に入るの一つの手づるになるかもしれません。しかし必ずしも大量の時間とエネルギーで復習しなくて、弊社が丹精にできあがった問題集を使って、試験なんて問題ではありません。

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Amazon MLS-C01資格講座 - 」とゴーリキーは述べました。

あなたが悲しいとき、勉強したほうがいいです。勉強があなたに無敵な位置に立たせます。RadiatoripermotoriのAmazonのMLS-C01資格講座試験トレーニング資料は同様にあなたに無敵な位置に立たせることができます。このトレーニング資料を手に入れたら、あなたは国際的に認可されたAmazonのMLS-C01資格講座認定試験に合格することができるようになります。そうしたら、金銭と地位を含むあなたの生活は向上させることができます。そのとき、あなたはまだ悲しいですか。いいえ、あなたはきっと非常に誇りに思うでしょう。Radiatoripermotoriがそんなに良いトレーニング資料を提供してあげることを感謝すべきです。Radiatoripermotoriはあなたが方途を失うときにヘルプを提供します。あなたの独自の品質を向上させるだけでなく、完璧な人生価値を実現することも助けます。

あなたの夢は何ですか。あなたのキャリアでいくつかの輝かしい業績を行うことを望まないのですか。

MLS-C01 PDF DEMO:

QUESTION NO: 1
A Machine Learning Specialist working for an online fashion company wants to build a data ingestion solution for the company's Amazon S3-based data lake.
The Specialist wants to create a set of ingestion mechanisms that will enable future capabilities comprised of:
* Real-time analytics
* Interactive analytics of historical data
* Clickstream analytics
* Product recommendations
Which services should the Specialist use?
A. Amazon Athena as the data catalog; Amazon Kinesis Data Streams and Amazon Kinesis Data
Analytics for historical data insights; Amazon DynamoDB streams for clickstream analytics; AWS Glue to generate personalized product recommendations
B. AWS Glue as the data catalog; Amazon Kinesis Data Streams and Amazon Kinesis Data Analytics for historical data insights; Amazon Kinesis Data Firehose for delivery to Amazon ES for clickstream analytics; Amazon EMR to generate personalized product recommendations
C. AWS Glue as the data dialog; Amazon Kinesis Data Streams and Amazon Kinesis Data Analytics for real-time data insights; Amazon Kinesis Data Firehose for delivery to Amazon ES for clickstream analytics; Amazon EMR to generate personalized product recommendations
D. Amazon Athena as the data catalog; Amazon Kinesis Data Streams and Amazon Kinesis Data
Analytics for near-realtime data insights; Amazon Kinesis Data Firehose for clickstream analytics; AWS
Glue to generate personalized product recommendations
Answer: C

QUESTION NO: 2
A Machine Learning Specialist has created a deep learning neural network model that performs well on the training data but performs poorly on the test data.
Which of the following methods should the Specialist consider using to correct this? (Select THREE.)
A. Decrease dropout.
B. Increase regularization.
C. Increase feature combinations.
D. Decrease feature combinations.
E. Decrease regularization.
F. Increase dropout.
Answer: A,B,C

QUESTION NO: 3
A Machine Learning Specialist built an image classification deep learning model. However the
Specialist ran into an overfitting problem in which the training and testing accuracies were 99% and
75%r respectively.
How should the Specialist address this issue and what is the reason behind it?
A. The learning rate should be increased because the optimization process was trapped at a local minimum.
B. The dimensionality of dense layer next to the flatten layer should be increased because the model is not complex enough.
C. The epoch number should be increased because the optimization process was terminated before it reached the global minimum.
D. The dropout rate at the flatten layer should be increased because the model is not generalized enough.
Answer: C

QUESTION NO: 4
A Machine Learning Specialist kicks off a hyperparameter tuning job for a tree-based ensemble model using Amazon SageMaker with Area Under the ROC Curve (AUC) as the objective metric This workflow will eventually be deployed in a pipeline that retrains and tunes hyperparameters each night to model click-through on data that goes stale every 24 hours With the goal of decreasing the amount of time it takes to train these models, and ultimately to decrease costs, the Specialist wants to reconfigure the input hyperparameter range(s) Which visualization will accomplish this?
A. A scatter plot with points colored by target variable that uses (-Distributed Stochastic Neighbor
Embedding (I-SNE) to visualize the large number of input variables in an easier-to-read dimension.
B. A scatter plot showing (he performance of the objective metric over each training iteration
C. A histogram showing whether the most important input feature is Gaussian.
D. A scatter plot showing the correlation between maximum tree depth and the objective metric.
Answer: A

QUESTION NO: 5
A Machine Learning Specialist receives customer data for an online shopping website. The data includes demographics, past visits, and locality information. The Specialist must develop a machine learning approach to identify the customer shopping patterns, preferences and trends to enhance the website for better service and smart recommendations.
Which solution should the Specialist recommend?
A. A neural network with a minimum of three layers and random initial weights to identify patterns in the customer database
B. Random Cut Forest (RCF) over random subsamples to identify patterns in the customer database
C. Latent Dirichlet Allocation (LDA) for the given collection of discrete data to identify patterns in the customer database.
D. Collaborative filtering based on user interactions and correlations to identify patterns in the customer database
Answer: D

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Updated: May 28, 2022